Neurocognitive and Neurophysiological Insights into Immersive Learning

Dear Colleagues,

This Special Issue explores the neural and physiological mechanisms underlying learning, attention, and knowledge acquisition across immersive, digital, and experiential environments. As virtual reality, 360° video, cinematic storytelling, and spatially rich audiovisual technologies increasingly mediate educational and cultural experiences, there is a growing scientific need to understand how the human brain encodes, consolidates, and retrieves information delivered through these formats. Neurophysiological methods, including electroencephalography (EEG), electrodermal activity (EDA), eye-tracking, fMRI, and fNIRS, can now provide objective, continuous indices of learner engagement, cognitive load, emotional arousal, and memory consolidation that extend well beyond what self-report measures alone can capture. Studies addressing clinical and neurorehabilitation populations, including individuals with cognitive impairment, neurodevelopmental conditions, or acquired brain injury, are equally welcome, as immersive and neurophysiological approaches increasingly bridge educational and therapeutic learning contexts.

For this collection, we encourage original research articles, systematic and narrative reviews, methodological papers, and theoretical contributions that address the neurophysiological and cognitive correlates of learning across immersive, cinematic, and digital media environments. Topics of interest include EEG-based engagement and attention markers, inter-subject neural synchrony (ISC) as a shared comprehension metric, memory encoding in immersive versus traditional media, affective neurolearning, multimodal biosignal fusion for real-time learner state monitoring, culturally situated and place-based cognitive neuroscience, individual differences in neural learning responses, and AI-driven neuroadaptive educational systems. Contributions spanning educational neuroscience, cognitive science, affective computing, and human–computer interaction are equally welcome.

This Special Issue covers the following thematic areas:

1. Neural Correlates of Attention, Engagement, and Motivation: Neurophysiological and cognitive bases of attentional focus, motivational drive, and sustained engagement as foundational preconditions for effective learning across diverse environments and populations.
2. Memory Encoding, Consolidation, and Knowledge Acquisition: Neural and physiological mechanisms underlying the formation, retention, and retrieval of knowledge, with attention to how learning format, context, and experience modulate these processes.
3. Cognitive Load, Neural Efficiency, and Mental Workload: Neurophysiological assessment of cognitive demand, mental effort, and processing efficiency during learning tasks, spanning traditional, digital, screen-based, and immersive instructional formats.
4. Neural Synchrony and Inter-Subject Correlation as Learning Metrics: Population-level indices of shared comprehension, communicative effectiveness, and collective knowledge formation derived from inter-subject correlation (ISC) and neural synchrony analysis.
5. Affective Neuroscience of Learning: The role of emotion, arousal, curiosity, awe, and motivational affect in modulating memory consolidation, attentional engagement, and long-term knowledge retention.
6. Immersive, Extended, and Emerging Reality Learning Environments: Neurophysiological and cognitive study of learning in virtual, augmented, mixed, and extended reality (VR/AR/MR/XR) settings, including presence, embodiment, and immersion as learning-relevant variables.
7. Individual Differences, Learner Diversity, and Clinical Neurolearning: How cultural background, prior knowledge, age, neurodevelopmental profiles, and clinical conditions—including cognitive impairment, acquired brain injury, ADHD, and neurorehabilitation needs—modulate neurophysiological learning responses, with implications for inclusive, personalised, and therapeutic educational design.
8. Situated, Place-Based, and Experiential Learning Contexts: Neurophysiological investigation of learning in outdoor, environmental, cultural, and community-embedded settings, including heritage education, nature-based instruction, and spatially situated cognitive experiences.
9. Multimodal Neurophysiological Assessment and Biosignal Integration: Methods and architectures for combining multiple biosignal streams—including EEG, electrodermal activity, eye-tracking, cardiac measures, and neuroimaging—for comprehensive, ecologically valid learner state monitoring.
10. Artificial Intelligence and Neuroadaptive Learning Systems: Machine learning, deep learning, and AI-driven approaches for real-time learner state classification, adaptive content delivery, and personalised educational intervention informed by neurophysiological data.

Dr. Constantinos Halkiopoulos
Dr. Evgenia Gkintoni
Guest Editors

Manuscript Submission Information

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